Download or read book Defense Against Test time Evasion Attacks and Backdoor Attacks written by Hang Wang and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep Neural networks (DNN) have been successfully applied to many areas. However, they have been shown to be vulnerable to adversarial attacks. One representative adversarial attack is the test time evasion attack (TTE attack, also known as adversarial example attack), which modifies a test sample with a small, sample-specific, and human imperceptible perturbation so that it is misclassified by the DNN classifier. The backdoor attack (Trojan) is another type of adversarial attack emerging recently. A backdoor attacker aims to inject a backdoor trigger (typically a universal pattern) into an attacked DNN classifier, such that the classifier will misclassify a test sample into a pre-designed target class whenever the backdoor trigger is present. A backdoor attack can be launched either by poisoning the training dataset or by controlling the training process. Both types of attacks are very harmful, especially in high-risk applications (like facial recognition authorization and traffic sign recognition in self-driving cars) where misclassification will lead to serious consequences. Defending against those attacks is important and challenging. To defend against the TTE attack, one can either robustify the DNN or detect the adversarial examples. One can attempt to robustify a DNN through adversarial training, certified training, or DNN embedding. Also, some adversarial examples can be identified using the internal layer activation features. Defense against backdoor attacks can be mounted at different stages. Pre-training (or during training) defenses aim to obtain a clean model given the potentially poisoned training set. Post-training defenses aim to either detect if a model is attacked or repair a potentially poisoned model to avoid misclassifications. Inference time defenses aim to detect or robustly classify a test sample with the backdoor trigger. In this thesis, we propose several defenses against TTE attacks and backdoor attacks. For TTE attacks, we proposed a conditional generative adversarial network based anomaly detection method (ACGAN-ADA). For backdoor attacks, we proposed a pre-training data cleansing method based on a contrastive learning method, which can cleanse the training set by filtering and relabeling the out-of-distribution training samples. Several defense schemes are also proposed post-training: A maximum classification-margin based backdoor detection method (MM-BD) is proposed to detect whether a model is attacked. The MM-BD method is based on the observation that the attacked model will overfit to the backdoor trigger, and thus be overconfident in the decision made on a sample with the backdoor trigger. MM-BD makes no assumption about the backdoor pattern type.

Download or read book Adversarial Learning and Secure AI written by David J. Miller and published by Cambridge University Press. This book was released on 2023-08-31 with total page 375 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first textbook on adversarial machine learning, including both attacks and defenses, background material, and hands-on student projects.

Download or read book Robust Machine Learning Algorithms and Systems for Detection and Mitigation of Adversarial Attacks and Anomalies written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2019-08-22 with total page 83 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Intelligence Community Studies Board (ICSB) of the National Academies of Sciences, Engineering, and Medicine convened a workshop on December 11â€"12, 2018, in Berkeley, California, to discuss robust machine learning algorithms and systems for the detection and mitigation of adversarial attacks and anomalies. This publication summarizes the presentations and discussions from the workshop.

Download or read book Cryptology and Network Security written by Mauro Conti and published by Springer Nature. This book was released on 2021-12-08 with total page 556 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 20th International Conference on Cryptology and Network Security, CANS 2021, which was held during December 13-15, 2021. The conference was originally planned to take place in Vienna, Austria, and changed to an online event due to the COVID-19 pandemic. The 25 full and 3 short papers presented in these proceedings were carefully reviewed and selected from 85 submissions. They were organized in topical sections as follows: Encryption; signatures; cryptographic schemes and protocols; attacks and counter-measures; and attestation and verification.

Download or read book Attacks Defenses and Testing for Deep Learning written by Jinyin Chen and published by Springer Nature. This book was released on with total page 413 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Implications of Artificial Intelligence for Cybersecurity written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2020-01-27 with total page 99 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, interest and progress in the area of artificial intelligence (AI) and machine learning (ML) have boomed, with new applications vigorously pursued across many sectors. At the same time, the computing and communications technologies on which we have come to rely present serious security concerns: cyberattacks have escalated in number, frequency, and impact, drawing increased attention to the vulnerabilities of cyber systems and the need to increase their security. In the face of this changing landscape, there is significant concern and interest among policymakers, security practitioners, technologists, researchers, and the public about the potential implications of AI and ML for cybersecurity. The National Academies of Sciences, Engineering, and Medicine convened a workshop on March 12-13, 2019 to discuss and explore these concerns. This publication summarizes the presentations and discussions from the workshop.

Download or read book Four Battlegrounds Power in the Age of Artificial Intelligence written by Paul Scharre and published by W. W. Norton & Company. This book was released on 2023-02-28 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: An NPR 2023 "Books We Love" Pick One of the Next Big Idea Club's Must-Read Books "An invaluable primer to arguably the most important driver of change for our future." —P. W. Singer, author of Burn-In An award-winning defense expert tells the story of today’s great power rivalry—the struggle to control artificial intelligence. A new industrial revolution has begun. Like mechanization or electricity before it, artificial intelligence will touch every aspect of our lives—and cause profound disruptions in the balance of global power, especially among the AI superpowers: China, the United States, and Europe. Autonomous weapons expert Paul Scharre takes readers inside the fierce competition to develop and implement this game-changing technology and dominate the future. Four Battlegrounds argues that four key elements define this struggle: data, computing power, talent, and institutions. Data is a vital resource like coal or oil, but it must be collected and refined. Advanced computer chips are the essence of computing power—control over chip supply chains grants leverage over rivals. Talent is about people: which country attracts the best researchers and most advanced technology companies? The fourth “battlefield” is maybe the most critical: the ultimate global leader in AI will have institutions that effectively incorporate AI into their economy, society, and especially their military. Scharre’s account surges with futuristic technology. He explores the ways AI systems are already discovering new strategies via millions of war-game simulations, developing combat tactics better than any human, tracking billions of people using biometrics, and subtly controlling information with secret algorithms. He visits China’s “National Team” of leading AI companies to show the chilling synergy between China’s government, private sector, and surveillance state. He interviews Pentagon leadership and tours U.S. Defense Department offices in Silicon Valley, revealing deep tensions between the military and tech giants who control data, chips, and talent. Yet he concludes that those tensions, inherent to our democratic system, create resilience and resistance to autocracy in the face of overwhelmingly powerful technology. Engaging and direct, Four Battlegrounds offers a vivid picture of how AI is transforming warfare, global security, and the future of human freedom—and what it will take for democracies to remain at the forefront of the world order.

Download or read book Game Theory and Machine Learning for Cyber Security written by Charles A. Kamhoua and published by John Wiley & Sons. This book was released on 2021-09-08 with total page 546 pages. Available in PDF, EPUB and Kindle. Book excerpt: GAME THEORY AND MACHINE LEARNING FOR CYBER SECURITY Move beyond the foundations of machine learning and game theory in cyber security to the latest research in this cutting-edge field In Game Theory and Machine Learning for Cyber Security, a team of expert security researchers delivers a collection of central research contributions from both machine learning and game theory applicable to cybersecurity. The distinguished editors have included resources that address open research questions in game theory and machine learning applied to cyber security systems and examine the strengths and limitations of current game theoretic models for cyber security. Readers will explore the vulnerabilities of traditional machine learning algorithms and how they can be mitigated in an adversarial machine learning approach. The book offers a comprehensive suite of solutions to a broad range of technical issues in applying game theory and machine learning to solve cyber security challenges. Beginning with an introduction to foundational concepts in game theory, machine learning, cyber security, and cyber deception, the editors provide readers with resources that discuss the latest in hypergames, behavioral game theory, adversarial machine learning, generative adversarial networks, and multi-agent reinforcement learning. Readers will also enjoy: A thorough introduction to game theory for cyber deception, including scalable algorithms for identifying stealthy attackers in a game theoretic framework, honeypot allocation over attack graphs, and behavioral games for cyber deception An exploration of game theory for cyber security, including actionable game-theoretic adversarial intervention detection against advanced persistent threats Practical discussions of adversarial machine learning for cyber security, including adversarial machine learning in 5G security and machine learning-driven fault injection in cyber-physical systems In-depth examinations of generative models for cyber security Perfect for researchers, students, and experts in the fields of computer science and engineering, Game Theory and Machine Learning for Cyber Security is also an indispensable resource for industry professionals, military personnel, researchers, faculty, and students with an interest in cyber security.

Download or read book Dynamic Data Driven Applications Systems written by Frederica Darema and published by Springer Nature. This book was released on 2020-11-02 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Third International Conference on Dynamic Data Driven Application Systems, DDDAS 2020, held in Boston, MA, USA, in October 2020. The 21 full papers and 14 short papers presented in this volume were carefully reviewed and selected from 40 submissions. They cover topics such as: digital twins; environment cognizant adaptive-planning systems; energy systems; materials systems; physics-based systems analysis; imaging methods and systems; and learning systems.

Download or read book Computer Vision ECCV 2020 Workshops written by Adrien Bartoli and published by Springer Nature. This book was released on 2021-01-09 with total page 818 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 6-volume set, comprising the LNCS books 12535 until 12540, constitutes the refereed proceedings of 28 out of the 45 workshops held at the 16th European Conference on Computer Vision, ECCV 2020. The conference was planned to take place in Glasgow, UK, during August 23-28, 2020, but changed to a virtual format due to the COVID-19 pandemic. The 249 full papers, 18 short papers, and 21 further contributions included in the workshop proceedings were carefully reviewed and selected from a total of 467 submissions. The papers deal with diverse computer vision topics. Part I focusses on adversarial robustness in the real world; bioimage computation; egocentric perception, interaction and computing; eye gaze in VR, AR, and in the wild; TASK-CV workshop and VisDA challenge; and bodily expressed emotion understanding.

Download or read book Research in Attacks Intrusions and Defenses written by Marc Dacier and published by Springer. This book was released on 2017-10-10 with total page 501 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed conference proceedings of the 20th International Symposium on Research in Attacks, Intrusions, and Defenses, RAID 2017, held in Atlanta, GA, USA, in September 2017. The 21 revised full papers were selected from 105 submissions. They are organized in the following topics: software security, intrusion detection, systems security, android security, cybercrime, cloud security, network security.

Download or read book AI Machine Learning and Deep Learning written by Fei Hu and published by CRC Press. This book was released on 2023-06-05 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: Today, Artificial Intelligence (AI) and Machine Learning/ Deep Learning (ML/DL) have become the hottest areas in information technology. In our society, many intelligent devices rely on AI/ML/DL algorithms/tools for smart operations. Although AI/ML/DL algorithms and tools have been used in many internet applications and electronic devices, they are also vulnerable to various attacks and threats. AI parameters may be distorted by the internal attacker; the DL input samples may be polluted by adversaries; the ML model may be misled by changing the classification boundary, among many other attacks and threats. Such attacks can make AI products dangerous to use. While this discussion focuses on security issues in AI/ML/DL-based systems (i.e., securing the intelligent systems themselves), AI/ML/DL models and algorithms can actually also be used for cyber security (i.e., the use of AI to achieve security). Since AI/ML/DL security is a newly emergent field, many researchers and industry professionals cannot yet obtain a detailed, comprehensive understanding of this area. This book aims to provide a complete picture of the challenges and solutions to related security issues in various applications. It explains how different attacks can occur in advanced AI tools and the challenges of overcoming those attacks. Then, the book describes many sets of promising solutions to achieve AI security and privacy. The features of this book have seven aspects: This is the first book to explain various practical attacks and countermeasures to AI systems Both quantitative math models and practical security implementations are provided It covers both "securing the AI system itself" and "using AI to achieve security" It covers all the advanced AI attacks and threats with detailed attack models It provides multiple solution spaces to the security and privacy issues in AI tools The differences among ML and DL security and privacy issues are explained Many practical security applications are covered

Download or read book Distributed Computer and Communication Networks written by Vladimir M. Vishnevskiy and published by Springer Nature. This book was released on 2023-04-30 with total page 391 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 25th International Conference on Distributed Computer and Communication Networks, DCCN 2022, held in Moscow, Russia, in September 2022. The 27 full papers and 2 short papers included in this book were carefully reviewed and selected from 130 submissions. They were organized in topical sections as follows: Distributed Systems Applications, Computer and Communication Networks, Analytical Modeling of Distributed Systems.

Download or read book Intelligent Security Systems written by Leon Reznik and published by John Wiley & Sons. This book was released on 2021-10-19 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: INTELLIGENT SECURITY SYSTEMS Dramatically improve your cybersecurity using AI and machine learning In Intelligent Security Systems, distinguished professor and computer scientist Dr. Leon Reznik delivers an expert synthesis of artificial intelligence, machine learning and data science techniques, applied to computer security to assist readers in hardening their computer systems against threats. Emphasizing practical and actionable strategies that can be immediately implemented by industry professionals and computer device’s owners, the author explains how to install and harden firewalls, intrusion detection systems, attack recognition tools, and malware protection systems. He also explains how to recognize and counter common hacking activities. This book bridges the gap between cybersecurity education and new data science programs, discussing how cutting-edge artificial intelligence and machine learning techniques can work for and against cybersecurity efforts. Intelligent Security Systems includes supplementary resources on an author-hosted website, such as classroom presentation slides, sample review, test and exam questions, and practice exercises to make the material contained practical and useful. The book also offers: A thorough introduction to computer security, artificial intelligence, and machine learning, including basic definitions and concepts like threats, vulnerabilities, risks, attacks, protection, and tools An exploration of firewall design and implementation, including firewall types and models, typical designs and configurations, and their limitations and problems Discussions of intrusion detection systems (IDS), including architecture topologies, components, and operational ranges, classification approaches, and machine learning techniques in IDS design A treatment of malware and vulnerabilities detection and protection, including malware classes, history, and development trends Perfect for undergraduate and graduate students in computer security, computer science and engineering, Intelligent Security Systems will also earn a place in the libraries of students and educators in information technology and data science, as well as professionals working in those fields.

Download or read book Malware Detection written by Mihai Christodorescu and published by Springer Science & Business Media. This book was released on 2007-03-06 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book captures the state of the art research in the area of malicious code detection, prevention and mitigation. It contains cutting-edge behavior-based techniques to analyze and detect obfuscated malware. The book analyzes current trends in malware activity online, including botnets and malicious code for profit, and it proposes effective models for detection and prevention of attacks using. Furthermore, the book introduces novel techniques for creating services that protect their own integrity and safety, plus the data they manage.

Download or read book Moving Target Defense written by Sushil Jajodia and published by Springer Science & Business Media. This book was released on 2011-08-26 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt: Moving Target Defense: Creating Asymmetric Uncertainty for Cyber Threats was developed by a group of leading researchers. It describes the fundamental challenges facing the research community and identifies new promising solution paths. Moving Target Defense which is motivated by the asymmetric costs borne by cyber defenders takes an advantage afforded to attackers and reverses it to advantage defenders. Moving Target Defense is enabled by technical trends in recent years, including virtualization and workload migration on commodity systems, widespread and redundant network connectivity, instruction set and address space layout randomization, just-in-time compilers, among other techniques. However, many challenging research problems remain to be solved, such as the security of virtualization infrastructures, secure and resilient techniques to move systems within a virtualized environment, automatic diversification techniques, automated ways to dynamically change and manage the configurations of systems and networks, quantification of security improvement, potential degradation and more. Moving Target Defense: Creating Asymmetric Uncertainty for Cyber Threats is designed for advanced -level students and researchers focused on computer science, and as a secondary text book or reference. Professionals working in this field will also find this book valuable.

Download or read book Resilience and Hybrid Threats written by I. Linkov and published by IOS Press. This book was released on 2019-12-19 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hybrid threats represent one of the rising challenges to the safe and effective management of digital systems worldwide. The deliberate misuse or disruption of digital technologies has wide-ranging implications for fields as diverse as medicine, social media, and homeland security. Despite growing concern about cyber threats within many government agencies and international organizations, few strategies for the effective avoidance and management of threats or the prevention of the disruption they can cause have so far emerged. This book presents multiple perspectives based upon a NATO Science for Peace and Security Programme Advanced Research Workshop on ‘Resilience and Hybrid Threats’ held in Pärnu, Estonia from 26-29 August 2018, and includes a mixture of workshop summary papers and invited perspectives from world experts. Topics include the development of strategies for the protection and recovery of systems affected by hybrid threats, and the benefits of those strategies under different disruption scenarios. The role of risk and resilience assessment pertaining to the information domain is a common focus across all perspectives. Offering an overview of resilience-based decision making through an approach that integrates the threats and dependencies related to infrastructural, informational, and social considerations, the book will be of interest to all those whose work involves the security of digital systems.